Regulation of Human Cardiac Ion Channel Genes by MicroRNAs: Theoretical Perspective and Pathophysiological Implications
Bibliographic record
Abstract
Excitability is a fundamental characteristic of cardiac cells, which is delicately determined by ion channel activities modulated by many factors. MicroRNA (miRNA) expression is dynamically regulated and altered miRNA expression can render expression deregulation of ion channel genes leading to channelopathies-arrhythmogenesis. Indeed, evidence has emerged indicating the crucial role of miRNAs in controlling cardiac excitability by regulating expression of ion channel genes at the post-transcriptional level. However, the very limited experimental data in the literature hinder our understanding of the role of miRNAs and the often one-to-one interaction between miRNA and ion-channel gene in the published studies also casts a doubt about fullness of our view. Unfortunately, currently available techniques do not permit thorough characterization of miRNA targeting; computational prediction programs remain the only source for rapid identification of a putative miRNA target in silico. We conducted a rationally designed bioinformatics analysis in conjunction with experimental approaches to identify the miRNAs from the currently available miRNA databases which have the potential to regulate human cardiac ion channel genes and to validate the analysis with several pathological settings associated with the deregulated miRNAs and ion channel genes in the heart. We established a matrix of miRNAs that are expressed in cardiac cells and have the potential to regulate the genes encoding cardiac ion channels and transporters. We were able to explain a particular ionic remodeling process in hypertrophy/heart failure, myocardial ischemia, or atrial fibrillation with the corresponding deregulated miRNAs under that pathological condition; the changes of miRNAs appear to have anti-correlation with the changes of many of the genes encoding cardiac ion channels under these situations. These results indicate that multiple miRNAs might be critically involved in the electrical/ionic remodeling processes of cardiac diseases through altering their expression in cardiac cells, which has not been uncovered by previous experimental studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".